Overview

Dataset statistics

Number of variables32
Number of observations12328
Missing cells438
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 MiB
Average record size in memory256.0 B

Variable types

Numeric28
Categorical4

Alerts

Player has a high cardinality: 2720 distinct values High cardinality
Nick has a high cardinality: 2723 distinct values High cardinality
Rk is highly correlated with GP and 15 other fieldsHigh correlation
GP is highly correlated with Rk and 14 other fieldsHigh correlation
G is highly correlated with Rk and 13 other fieldsHigh correlation
A is highly correlated with Rk and 15 other fieldsHigh correlation
PTS is highly correlated with Rk and 15 other fieldsHigh correlation
PIM is highly correlated with GPHigh correlation
PS is highly correlated with Rk and 15 other fieldsHigh correlation
EV is highly correlated with Rk and 12 other fieldsHigh correlation
PP is highly correlated with Rk and 10 other fieldsHigh correlation
GW is highly correlated with Rk and 11 other fieldsHigh correlation
EV.1 is highly correlated with Rk and 14 other fieldsHigh correlation
PP.1 is highly correlated with Rk and 12 other fieldsHigh correlation
S is highly correlated with Rk and 13 other fieldsHigh correlation
S_percent is highly correlated with G and 1 other fieldsHigh correlation
TOI is highly correlated with Rk and 15 other fieldsHigh correlation
ATOI is highly correlated with Rk and 10 other fieldsHigh correlation
BLK is highly correlated with Rk and 3 other fieldsHigh correlation
HIT is highly correlated with Rk and 3 other fieldsHigh correlation
FOW is highly correlated with FOL and 1 other fieldsHigh correlation
FOL is highly correlated with FOW and 1 other fieldsHigh correlation
FO_percent is highly correlated with FOW and 1 other fieldsHigh correlation
Season is highly correlated with RkHigh correlation
HART is highly correlated with A and 3 other fieldsHigh correlation
Votes is highly correlated with G and 7 other fieldsHigh correlation
plusminus is highly correlated with GP and 5 other fieldsHigh correlation
S_percent has 124 (1.0%) missing values Missing
FO_percent has 311 (2.5%) missing values Missing
HART is highly skewed (γ1 = 29.62745631) Skewed
Votes is highly skewed (γ1 = 20.04010988) Skewed
G has 2685 (21.8%) zeros Zeros
A has 1851 (15.0%) zeros Zeros
PTS has 1486 (12.1%) zeros Zeros
plusminus has 1191 (9.7%) zeros Zeros
PIM has 1257 (10.2%) zeros Zeros
PS has 874 (7.1%) zeros Zeros
EV has 2878 (23.3%) zeros Zeros
PP has 6929 (56.2%) zeros Zeros
SH has 10389 (84.3%) zeros Zeros
GW has 6376 (51.7%) zeros Zeros
EV.1 has 1981 (16.1%) zeros Zeros
PP.1 has 6064 (49.2%) zeros Zeros
SH.1 has 10042 (81.5%) zeros Zeros
S has 397 (3.2%) zeros Zeros
S_percent has 2561 (20.8%) zeros Zeros
BLK has 3216 (26.1%) zeros Zeros
HIT has 2875 (23.3%) zeros Zeros
FOW has 6860 (55.6%) zeros Zeros
FOL has 6441 (52.2%) zeros Zeros
FO_percent has 6550 (53.1%) zeros Zeros
HART has 12314 (99.9%) zeros Zeros
Votes has 12211 (99.1%) zeros Zeros

Reproduction

Analysis started2022-11-15 10:47:44.117486
Analysis finished2022-11-15 10:50:24.389208
Duration2 minutes and 40.27 seconds
Software versionpandas-profiling v3.4.0
Download configurationconfig.json

Variables

Rk
Real number (ℝ≥0)

HIGH CORRELATION

Distinct2644
Distinct (%)21.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean629.9415964
Minimum1
Maximum2644
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size96.4 KiB
2022-11-15T11:50:24.601117image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile52
Q1257
median514
Q3771
95-th percentile2027.65
Maximum2644
Range2643
Interquartile range (IQR)514

Descriptive statistics

Standard deviation553.8710142
Coefficient of variation (CV)0.8792418494
Kurtosis2.929074408
Mean629.9415964
Median Absolute Deviation (MAD)257
Skewness1.746762923
Sum7765920
Variance306773.1003
MonotonicityNot monotonic
2022-11-15T11:50:24.797560image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
112
 
0.1%
57812
 
0.1%
55412
 
0.1%
55512
 
0.1%
55612
 
0.1%
55712
 
0.1%
55812
 
0.1%
55912
 
0.1%
56012
 
0.1%
56112
 
0.1%
Other values (2634)12208
99.0%
ValueCountFrequency (%)
112
0.1%
212
0.1%
312
0.1%
412
0.1%
512
0.1%
612
0.1%
712
0.1%
812
0.1%
912
0.1%
1012
0.1%
ValueCountFrequency (%)
26441
< 0.1%
26431
< 0.1%
26421
< 0.1%
26411
< 0.1%
26401
< 0.1%
26391
< 0.1%
26381
< 0.1%
26371
< 0.1%
26361
< 0.1%
26351
< 0.1%

Player
Categorical

HIGH CARDINALITY

Distinct2720
Distinct (%)22.1%
Missing0
Missing (%)0.0%
Memory size96.4 KiB
Mike Fisher
 
14
Brooks Orpik
 
14
Henrik Zetterberg
 
14
Trevor Daley
 
14
Ales Hemsky
 
14
Other values (2715)
12258 

Length

Max length29
Median length22
Mean length12.89203439
Min length7

Characters and Unicode

Total characters158933
Distinct characters58
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique646 ?
Unique (%)5.2%

Sample

1st rowConnor McDavid
2nd rowSidney Crosby
3rd rowPatrick Kane
4th rowNicklas Backstrom
5th rowNikita Kucherov

Common Values

ValueCountFrequency (%)
Mike Fisher14
 
0.1%
Brooks Orpik14
 
0.1%
Henrik Zetterberg14
 
0.1%
Trevor Daley14
 
0.1%
Ales Hemsky14
 
0.1%
Jason Chimera14
 
0.1%
Eric Staal14
 
0.1%
Daniel Sedin14
 
0.1%
Scottie Upshall14
 
0.1%
Patrick Sharp14
 
0.1%
Other values (2710)12188
98.9%

Length

2022-11-15T11:50:24.985177image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ryan302
 
1.2%
matt293
 
1.2%
mike267
 
1.1%
chris230
 
0.9%
mark175
 
0.7%
david173
 
0.7%
jason142
 
0.6%
eric131
 
0.5%
andrew127
 
0.5%
brian123
 
0.5%
Other values (2938)22788
92.1%

Most occurring characters

ValueCountFrequency (%)
e13858
 
8.7%
a13648
 
8.6%
12423
 
7.8%
n11305
 
7.1%
r11199
 
7.0%
i10067
 
6.3%
o9133
 
5.7%
l7202
 
4.5%
t6573
 
4.1%
s5872
 
3.7%
Other values (48)57653
36.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter120561
75.9%
Uppercase Letter25372
 
16.0%
Space Separator12423
 
7.8%
Other Punctuation455
 
0.3%
Dash Punctuation122
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e13858
11.5%
a13648
11.3%
n11305
9.4%
r11199
9.3%
i10067
 
8.4%
o9133
 
7.6%
l7202
 
6.0%
t6573
 
5.5%
s5872
 
4.9%
k3799
 
3.2%
Other values (16)27905
23.1%
Uppercase Letter
ValueCountFrequency (%)
M2725
 
10.7%
S2224
 
8.8%
B2189
 
8.6%
J2069
 
8.2%
C1696
 
6.7%
D1533
 
6.0%
R1369
 
5.4%
P1334
 
5.3%
A1326
 
5.2%
K1242
 
4.9%
Other values (16)7665
30.2%
Other Punctuation
ValueCountFrequency (%)
.249
54.7%
*113
24.8%
'85
 
18.7%
?8
 
1.8%
Space Separator
ValueCountFrequency (%)
12423
100.0%
Dash Punctuation
ValueCountFrequency (%)
-122
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin145933
91.8%
Common13000
 
8.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e13858
 
9.5%
a13648
 
9.4%
n11305
 
7.7%
r11199
 
7.7%
i10067
 
6.9%
o9133
 
6.3%
l7202
 
4.9%
t6573
 
4.5%
s5872
 
4.0%
k3799
 
2.6%
Other values (42)53277
36.5%
Common
ValueCountFrequency (%)
12423
95.6%
.249
 
1.9%
-122
 
0.9%
*113
 
0.9%
'85
 
0.7%
?8
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII158933
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e13858
 
8.7%
a13648
 
8.6%
12423
 
7.8%
n11305
 
7.1%
r11199
 
7.0%
i10067
 
6.3%
o9133
 
5.7%
l7202
 
4.5%
t6573
 
4.1%
s5872
 
3.7%
Other values (48)57653
36.3%

Nick
Categorical

HIGH CARDINALITY

Distinct2723
Distinct (%)22.1%
Missing0
Missing (%)0.0%
Memory size96.4 KiB
bouwmja01
 
14
staaler01
 
14
kunitch01
 
14
sharppa01
 
14
keslery01
 
14
Other values (2718)
12258 

Length

Max length9
Median length9
Mean length8.922534069
Min length7

Characters and Unicode

Total characters109997
Distinct characters34
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique642 ?
Unique (%)5.2%

Sample

1st rowmcdavco01
2nd rowcrosbsi01
3rd rowkanepa01
4th rowbacksni02
5th rowkucheni01

Common Values

ValueCountFrequency (%)
bouwmja0114
 
0.1%
staaler0114
 
0.1%
kunitch0114
 
0.1%
sharppa0114
 
0.1%
keslery0114
 
0.1%
hartnsc0114
 
0.1%
pominja0114
 
0.1%
stajama0114
 
0.1%
vrbatra0114
 
0.1%
fishemi0114
 
0.1%
Other values (2713)12188
98.9%

Length

2022-11-15T11:50:25.167324image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
bouwmja0114
 
0.1%
spezzja0114
 
0.1%
giontbr0114
 
0.1%
williju0114
 
0.1%
vermean0114
 
0.1%
marlepa0114
 
0.1%
orpikbr0114
 
0.1%
hainsro0114
 
0.1%
burnsbr0114
 
0.1%
cullema0114
 
0.1%
Other values (2713)12188
98.9%

Most occurring characters

ValueCountFrequency (%)
012328
 
11.2%
111833
 
10.8%
a10202
 
9.3%
e7297
 
6.6%
r6968
 
6.3%
o6085
 
5.5%
i5538
 
5.0%
l4961
 
4.5%
s4507
 
4.1%
n4336
 
3.9%
Other values (24)35942
32.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter85337
77.6%
Decimal Number24656
 
22.4%
Other Punctuation4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a10202
 
12.0%
e7297
 
8.6%
r6968
 
8.2%
o6085
 
7.1%
i5538
 
6.5%
l4961
 
5.8%
s4507
 
5.3%
n4336
 
5.1%
m3986
 
4.7%
t3938
 
4.6%
Other values (16)27519
32.2%
Decimal Number
ValueCountFrequency (%)
012328
50.0%
111833
48.0%
2394
 
1.6%
366
 
0.3%
518
 
0.1%
410
 
< 0.1%
67
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
.4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin85337
77.6%
Common24660
 
22.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a10202
 
12.0%
e7297
 
8.6%
r6968
 
8.2%
o6085
 
7.1%
i5538
 
6.5%
l4961
 
5.8%
s4507
 
5.3%
n4336
 
5.1%
m3986
 
4.7%
t3938
 
4.6%
Other values (16)27519
32.2%
Common
ValueCountFrequency (%)
012328
50.0%
111833
48.0%
2394
 
1.6%
366
 
0.3%
518
 
0.1%
410
 
< 0.1%
67
 
< 0.1%
.4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII109997
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
012328
 
11.2%
111833
 
10.8%
a10202
 
9.3%
e7297
 
6.6%
r6968
 
6.3%
o6085
 
5.5%
i5538
 
5.0%
l4961
 
4.5%
s4507
 
4.1%
n4336
 
3.9%
Other values (24)35942
32.7%

Age
Real number (ℝ≥0)

Distinct32
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.64073653
Minimum0
Maximum48
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size96.4 KiB
2022-11-15T11:50:25.355528image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile20
Q123
median26
Q330
95-th percentile35
Maximum48
Range48
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.582777694
Coefficient of variation (CV)0.1720214337
Kurtosis-0.03213778023
Mean26.64073653
Median Absolute Deviation (MAD)3
Skewness0.5902670802
Sum328427
Variance21.00185139
MonotonicityNot monotonic
2022-11-15T11:50:25.536685image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
231154
 
9.4%
241121
 
9.1%
251066
 
8.6%
26979
 
7.9%
22964
 
7.8%
27919
 
7.5%
28808
 
6.6%
21730
 
5.9%
29705
 
5.7%
30642
 
5.2%
Other values (22)3240
26.3%
ValueCountFrequency (%)
01
 
< 0.1%
1846
 
0.4%
19182
 
1.5%
20470
3.8%
21730
5.9%
22964
7.8%
231154
9.4%
241121
9.1%
251066
8.6%
26979
7.9%
ValueCountFrequency (%)
481
 
< 0.1%
471
 
< 0.1%
461
 
< 0.1%
452
 
< 0.1%
442
 
< 0.1%
435
 
< 0.1%
426
 
< 0.1%
4111
 
0.1%
4029
0.2%
3952
0.4%

Pos
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size96.4 KiB
D
4219 
C
3556 
LW
2279 
RW
2266 
C/LW
 
3
Other values (4)
 
5

Length

Max length5
Median length1
Mean length1.370619727
Min length1

Characters and Unicode

Total characters16897
Distinct characters6
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st rowC
2nd rowC
3rd rowRW
4th rowC
5th rowRW

Common Values

ValueCountFrequency (%)
D4219
34.2%
C3556
28.8%
LW2279
18.5%
RW2266
18.4%
C/LW3
 
< 0.1%
LW/RW2
 
< 0.1%
LW/C1
 
< 0.1%
RW/LW1
 
< 0.1%
W1
 
< 0.1%

Length

2022-11-15T11:50:25.729402image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-11-15T11:50:25.928198image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
d4219
34.2%
c3556
28.8%
lw2279
18.5%
rw2266
18.4%
c/lw3
 
< 0.1%
lw/rw2
 
< 0.1%
lw/c1
 
< 0.1%
rw/lw1
 
< 0.1%
w1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
W4556
27.0%
D4219
25.0%
C3560
21.1%
L2286
13.5%
R2269
13.4%
/7
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter16890
> 99.9%
Other Punctuation7
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
W4556
27.0%
D4219
25.0%
C3560
21.1%
L2286
13.5%
R2269
13.4%
Other Punctuation
ValueCountFrequency (%)
/7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin16890
> 99.9%
Common7
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
W4556
27.0%
D4219
25.0%
C3560
21.1%
L2286
13.5%
R2269
13.4%
Common
ValueCountFrequency (%)
/7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII16897
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
W4556
27.0%
D4219
25.0%
C3560
21.1%
L2286
13.5%
R2269
13.4%
/7
 
< 0.1%

Tm
Categorical

Distinct35
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size96.4 KiB
TOT
1030 
NYI
 
405
VAN
 
402
CBJ
 
398
EDM
 
396
Other values (30)
9697 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters36984
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEDM
2nd rowPIT
3rd rowCHI
4th rowWSH
5th rowTBL

Common Values

ValueCountFrequency (%)
TOT1030
 
8.4%
NYI405
 
3.3%
VAN402
 
3.3%
CBJ398
 
3.2%
EDM396
 
3.2%
NJD395
 
3.2%
WSH391
 
3.2%
BUF387
 
3.1%
TOR383
 
3.1%
MIN383
 
3.1%
Other values (25)7758
62.9%

Length

2022-11-15T11:50:26.107444image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tot1030
 
8.4%
nyi405
 
3.3%
van402
 
3.3%
cbj398
 
3.2%
edm396
 
3.2%
njd395
 
3.2%
wsh391
 
3.2%
buf387
 
3.1%
pit383
 
3.1%
tor383
 
3.1%
Other values (25)7758
62.9%

Most occurring characters

ValueCountFrequency (%)
T5238
14.2%
A2795
 
7.6%
L2751
 
7.4%
N2612
 
7.1%
O2544
 
6.9%
S2198
 
5.9%
I2034
 
5.5%
C1891
 
5.1%
H1767
 
4.8%
D1575
 
4.3%
Other values (14)11579
31.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter36984
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T5238
14.2%
A2795
 
7.6%
L2751
 
7.4%
N2612
 
7.1%
O2544
 
6.9%
S2198
 
5.9%
I2034
 
5.5%
C1891
 
5.1%
H1767
 
4.8%
D1575
 
4.3%
Other values (14)11579
31.3%

Most occurring scripts

ValueCountFrequency (%)
Latin36984
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
T5238
14.2%
A2795
 
7.6%
L2751
 
7.4%
N2612
 
7.1%
O2544
 
6.9%
S2198
 
5.9%
I2034
 
5.5%
C1891
 
5.1%
H1767
 
4.8%
D1575
 
4.3%
Other values (14)11579
31.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII36984
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
T5238
14.2%
A2795
 
7.6%
L2751
 
7.4%
N2612
 
7.1%
O2544
 
6.9%
S2198
 
5.9%
I2034
 
5.5%
C1891
 
5.1%
H1767
 
4.8%
D1575
 
4.3%
Other values (14)11579
31.3%

GP
Real number (ℝ≥0)

HIGH CORRELATION

Distinct84
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48.90274173
Minimum1
Maximum84
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size96.4 KiB
2022-11-15T11:50:26.304457image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q121
median57
Q376
95-th percentile82
Maximum84
Range83
Interquartile range (IQR)55

Descriptive statistics

Standard deviation28.66608331
Coefficient of variation (CV)0.5861856064
Kurtosis-1.339201444
Mean48.90274173
Median Absolute Deviation (MAD)22
Skewness-0.411605162
Sum602873
Variance821.7443325
MonotonicityNot monotonic
2022-11-15T11:50:26.677780image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
821141
 
9.3%
81513
 
4.2%
1427
 
3.5%
80406
 
3.3%
2343
 
2.8%
79328
 
2.7%
78280
 
2.3%
76268
 
2.2%
77264
 
2.1%
3264
 
2.1%
Other values (74)8094
65.7%
ValueCountFrequency (%)
1427
3.5%
2343
2.8%
3264
2.1%
4207
1.7%
5187
1.5%
6175
1.4%
7177
1.4%
8121
 
1.0%
9156
 
1.3%
10122
 
1.0%
ValueCountFrequency (%)
846
 
< 0.1%
8312
 
0.1%
821141
9.3%
81513
4.2%
80406
 
3.3%
79328
 
2.7%
78280
 
2.3%
77264
 
2.1%
76268
 
2.2%
75218
 
1.8%

G
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct58
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.484263465
Minimum0
Maximum65
Zeros2685
Zeros (%)21.8%
Negative0
Negative (%)0.0%
Memory size96.4 KiB
2022-11-15T11:50:26.886111image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median4
Q311
95-th percentile26
Maximum65
Range65
Interquartile range (IQR)10

Descriptive statistics

Standard deviation8.846935549
Coefficient of variation (CV)1.182071635
Kurtosis2.588049149
Mean7.484263465
Median Absolute Deviation (MAD)4
Skewness1.594192797
Sum92266
Variance78.26826861
MonotonicityNot monotonic
2022-11-15T11:50:27.076010image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
02685
21.8%
11369
 
11.1%
2975
 
7.9%
3750
 
6.1%
4672
 
5.5%
5542
 
4.4%
6510
 
4.1%
7419
 
3.4%
8406
 
3.3%
9327
 
2.7%
Other values (48)3673
29.8%
ValueCountFrequency (%)
02685
21.8%
11369
11.1%
2975
 
7.9%
3750
 
6.1%
4672
 
5.5%
5542
 
4.4%
6510
 
4.1%
7419
 
3.4%
8406
 
3.3%
9327
 
2.7%
ValueCountFrequency (%)
651
 
< 0.1%
601
 
< 0.1%
562
 
< 0.1%
541
 
< 0.1%
531
 
< 0.1%
524
< 0.1%
513
< 0.1%
507
0.1%
491
 
< 0.1%
482
 
< 0.1%

A
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct78
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.78771901
Minimum0
Maximum96
Zeros1851
Zeros (%)15.0%
Negative0
Negative (%)0.0%
Memory size96.4 KiB
2022-11-15T11:50:27.282286image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median9
Q320
95-th percentile39
Maximum96
Range96
Interquartile range (IQR)18

Descriptive statistics

Standard deviation13.12949606
Coefficient of variation (CV)1.026726975
Kurtosis1.651672529
Mean12.78771901
Median Absolute Deviation (MAD)8
Skewness1.310781942
Sum157647
Variance172.3836668
MonotonicityNot monotonic
2022-11-15T11:50:27.481410image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
01851
 
15.0%
1902
 
7.3%
2664
 
5.4%
3499
 
4.0%
5474
 
3.8%
6468
 
3.8%
4445
 
3.6%
7381
 
3.1%
8373
 
3.0%
10347
 
2.8%
Other values (68)5924
48.1%
ValueCountFrequency (%)
01851
15.0%
1902
7.3%
2664
 
5.4%
3499
 
4.0%
4445
 
3.6%
5474
 
3.8%
6468
 
3.8%
7381
 
3.1%
8373
 
3.0%
9344
 
2.8%
ValueCountFrequency (%)
961
 
< 0.1%
921
 
< 0.1%
841
 
< 0.1%
831
 
< 0.1%
781
 
< 0.1%
751
 
< 0.1%
741
 
< 0.1%
712
< 0.1%
702
< 0.1%
693
< 0.1%

PTS
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct116
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.27198248
Minimum0
Maximum125
Zeros1486
Zeros (%)12.1%
Negative0
Negative (%)0.0%
Memory size96.4 KiB
2022-11-15T11:50:27.665331image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median14
Q332
95-th percentile62
Maximum125
Range125
Interquartile range (IQR)29

Descriptive statistics

Standard deviation20.77847527
Coefficient of variation (CV)1.024984867
Kurtosis1.178863447
Mean20.27198248
Median Absolute Deviation (MAD)12
Skewness1.24284314
Sum249913
Variance431.7450347
MonotonicityNot monotonic
2022-11-15T11:50:27.876634image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
01486
 
12.1%
1775
 
6.3%
2542
 
4.4%
3414
 
3.4%
4384
 
3.1%
7318
 
2.6%
6310
 
2.5%
5309
 
2.5%
8293
 
2.4%
9278
 
2.3%
Other values (106)7219
58.6%
ValueCountFrequency (%)
01486
12.1%
1775
6.3%
2542
 
4.4%
3414
 
3.4%
4384
 
3.1%
5309
 
2.5%
6310
 
2.5%
7318
 
2.6%
8293
 
2.4%
9278
 
2.3%
ValueCountFrequency (%)
1251
 
< 0.1%
1231
 
< 0.1%
1201
 
< 0.1%
1141
 
< 0.1%
1131
 
< 0.1%
1122
< 0.1%
1101
 
< 0.1%
1093
< 0.1%
1082
< 0.1%
1063
< 0.1%

plusminus
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct88
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.3518007787
Minimum-46
Maximum50
Zeros1191
Zeros (%)9.7%
Negative6302
Negative (%)51.1%
Memory size96.4 KiB
2022-11-15T11:50:28.075462image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum-46
5-th percentile-15
Q1-5
median-1
Q34
95-th percentile17
Maximum50
Range96
Interquartile range (IQR)9

Descriptive statistics

Standard deviation9.414649018
Coefficient of variation (CV)-26.76130807
Kurtosis2.114386797
Mean-0.3518007787
Median Absolute Deviation (MAD)4
Skewness0.3954569445
Sum-4337
Variance88.63561613
MonotonicityNot monotonic
2022-11-15T11:50:28.266908image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
01191
 
9.7%
-11001
 
8.1%
-2792
 
6.4%
1779
 
6.3%
-3632
 
5.1%
-4542
 
4.4%
2527
 
4.3%
-5458
 
3.7%
3440
 
3.6%
-6381
 
3.1%
Other values (78)5585
45.3%
ValueCountFrequency (%)
-461
 
< 0.1%
-421
 
< 0.1%
-391
 
< 0.1%
-381
 
< 0.1%
-371
 
< 0.1%
-362
 
< 0.1%
-355
< 0.1%
-347
0.1%
-334
< 0.1%
-324
< 0.1%
ValueCountFrequency (%)
501
 
< 0.1%
491
 
< 0.1%
471
 
< 0.1%
451
 
< 0.1%
421
 
< 0.1%
411
 
< 0.1%
403
< 0.1%
392
< 0.1%
383
< 0.1%
374
< 0.1%

PIM
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct216
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.97112265
Minimum0
Maximum324
Zeros1257
Zeros (%)10.2%
Negative0
Negative (%)0.0%
Memory size96.4 KiB
2022-11-15T11:50:28.455507image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18
median24
Q345
95-th percentile93
Maximum324
Range324
Interquartile range (IQR)37

Descriptive statistics

Standard deviation32.31464886
Coefficient of variation (CV)1.010744891
Kurtosis6.212497044
Mean31.97112265
Median Absolute Deviation (MAD)18
Skewness1.963756878
Sum394140
Variance1044.236531
MonotonicityNot monotonic
2022-11-15T11:50:28.669009image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
01257
 
10.2%
2692
 
5.6%
4506
 
4.1%
6361
 
2.9%
8344
 
2.8%
14337
 
2.7%
16326
 
2.6%
18324
 
2.6%
12323
 
2.6%
20320
 
2.6%
Other values (206)7538
61.1%
ValueCountFrequency (%)
01257
10.2%
2692
5.6%
4506
4.1%
563
 
0.5%
6361
 
2.9%
768
 
0.6%
8344
 
2.8%
951
 
0.4%
10303
 
2.5%
1146
 
0.4%
ValueCountFrequency (%)
3241
< 0.1%
3071
< 0.1%
2651
< 0.1%
2611
< 0.1%
2571
< 0.1%
2541
< 0.1%
2501
< 0.1%
2471
< 0.1%
2391
< 0.1%
2381
< 0.1%

PS
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct163
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.48006976
Minimum-1.9
Maximum17.2
Zeros874
Zeros (%)7.1%
Negative1710
Negative (%)13.9%
Memory size96.4 KiB
2022-11-15T11:50:28.864363image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum-1.9
5-th percentile-0.2
Q10.2
median1.6
Q34.1
95-th percentile8.1
Maximum17.2
Range19.1
Interquartile range (IQR)3.9

Descriptive statistics

Standard deviation2.813307752
Coefficient of variation (CV)1.134366378
Kurtosis0.9955186664
Mean2.48006976
Median Absolute Deviation (MAD)1.6
Skewness1.193035551
Sum30574.3
Variance7.914700506
MonotonicityNot monotonic
2022-11-15T11:50:29.064543image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0874
 
7.1%
-0.1763
 
6.2%
0.1482
 
3.9%
0.2455
 
3.7%
-0.2367
 
3.0%
0.3318
 
2.6%
0.4278
 
2.3%
0.6261
 
2.1%
0.7226
 
1.8%
0.8213
 
1.7%
Other values (153)8091
65.6%
ValueCountFrequency (%)
-1.91
 
< 0.1%
-1.61
 
< 0.1%
-1.42
 
< 0.1%
-1.28
 
0.1%
-1.18
 
0.1%
-19
 
0.1%
-0.918
 
0.1%
-0.824
0.2%
-0.740
0.3%
-0.658
0.5%
ValueCountFrequency (%)
17.21
< 0.1%
15.71
< 0.1%
15.61
< 0.1%
15.51
< 0.1%
15.31
< 0.1%
151
< 0.1%
14.71
< 0.1%
14.61
< 0.1%
14.51
< 0.1%
14.41
< 0.1%

EV
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct41
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.387167424
Minimum0
Maximum48
Zeros2878
Zeros (%)23.3%
Negative0
Negative (%)0.0%
Memory size96.4 KiB
2022-11-15T11:50:29.258829image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q38
95-th percentile18
Maximum48
Range48
Interquartile range (IQR)7

Descriptive statistics

Standard deviation6.127264002
Coefficient of variation (CV)1.137381395
Kurtosis2.111036936
Mean5.387167424
Median Absolute Deviation (MAD)3
Skewness1.476669255
Sum66413
Variance37.54336415
MonotonicityNot monotonic
2022-11-15T11:50:29.463212image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
02878
23.3%
11577
12.8%
21121
 
9.1%
3879
 
7.1%
4795
 
6.4%
5620
 
5.0%
6539
 
4.4%
7479
 
3.9%
8422
 
3.4%
9411
 
3.3%
Other values (31)2607
21.1%
ValueCountFrequency (%)
02878
23.3%
11577
12.8%
21121
 
9.1%
3879
 
7.1%
4795
 
6.4%
5620
 
5.0%
6539
 
4.4%
7479
 
3.9%
8422
 
3.4%
9411
 
3.3%
ValueCountFrequency (%)
481
 
< 0.1%
431
 
< 0.1%
381
 
< 0.1%
371
 
< 0.1%
362
 
< 0.1%
353
< 0.1%
341
 
< 0.1%
331
 
< 0.1%
325
< 0.1%
317
0.1%

PP
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct27
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.859182349
Minimum0
Maximum27
Zeros6929
Zeros (%)56.2%
Negative0
Negative (%)0.0%
Memory size96.4 KiB
2022-11-15T11:50:29.824502image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile9
Maximum27
Range27
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.182269425
Coefficient of variation (CV)1.711649977
Kurtosis6.512352693
Mean1.859182349
Median Absolute Deviation (MAD)0
Skewness2.341644717
Sum22920
Variance10.12683869
MonotonicityNot monotonic
2022-11-15T11:50:30.017061image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
06929
56.2%
11437
 
11.7%
2862
 
7.0%
3646
 
5.2%
4502
 
4.1%
5439
 
3.6%
6348
 
2.8%
7265
 
2.1%
8232
 
1.9%
9154
 
1.2%
Other values (17)514
 
4.2%
ValueCountFrequency (%)
06929
56.2%
11437
 
11.7%
2862
 
7.0%
3646
 
5.2%
4502
 
4.1%
5439
 
3.6%
6348
 
2.8%
7265
 
2.1%
8232
 
1.9%
9154
 
1.2%
ValueCountFrequency (%)
271
 
< 0.1%
252
 
< 0.1%
245
 
< 0.1%
231
 
< 0.1%
221
 
< 0.1%
211
 
< 0.1%
203
 
< 0.1%
1910
0.1%
1810
0.1%
1718
0.1%

SH
Real number (ℝ≥0)

ZEROS

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2379136924
Minimum0
Maximum8
Zeros10389
Zeros (%)84.3%
Negative0
Negative (%)0.0%
Memory size96.4 KiB
2022-11-15T11:50:30.186820image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum8
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.6630386684
Coefficient of variation (CV)2.786887386
Kurtosis20.71849619
Mean0.2379136924
Median Absolute Deviation (MAD)0
Skewness3.932320034
Sum2933
Variance0.4396202758
MonotonicityNot monotonic
2022-11-15T11:50:30.347806image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
010389
84.3%
11317
 
10.7%
2394
 
3.2%
3137
 
1.1%
457
 
0.5%
524
 
0.2%
77
 
0.1%
62
 
< 0.1%
81
 
< 0.1%
ValueCountFrequency (%)
010389
84.3%
11317
 
10.7%
2394
 
3.2%
3137
 
1.1%
457
 
0.5%
524
 
0.2%
62
 
< 0.1%
77
 
0.1%
81
 
< 0.1%
ValueCountFrequency (%)
81
 
< 0.1%
77
 
0.1%
62
 
< 0.1%
524
 
0.2%
457
 
0.5%
3137
 
1.1%
2394
 
3.2%
11317
 
10.7%
010389
84.3%

GW
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.19151525
Minimum0
Maximum12
Zeros6376
Zeros (%)51.7%
Negative0
Negative (%)0.0%
Memory size96.4 KiB
2022-11-15T11:50:30.516850image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile5
Maximum12
Range12
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.760108713
Coefficient of variation (CV)1.477202002
Kurtosis4.35950104
Mean1.19151525
Median Absolute Deviation (MAD)0
Skewness1.962086301
Sum14689
Variance3.09798268
MonotonicityNot monotonic
2022-11-15T11:50:30.685759image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
06376
51.7%
12426
 
19.7%
21352
 
11.0%
3838
 
6.8%
4551
 
4.5%
5345
 
2.8%
6204
 
1.7%
7106
 
0.9%
869
 
0.6%
931
 
0.3%
Other values (3)30
 
0.2%
ValueCountFrequency (%)
06376
51.7%
12426
 
19.7%
21352
 
11.0%
3838
 
6.8%
4551
 
4.5%
5345
 
2.8%
6204
 
1.7%
7106
 
0.9%
869
 
0.6%
931
 
0.3%
ValueCountFrequency (%)
125
 
< 0.1%
119
 
0.1%
1016
 
0.1%
931
 
0.3%
869
 
0.6%
7106
 
0.9%
6204
 
1.7%
5345
2.8%
4551
4.5%
3838
6.8%

EV.1
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct52
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.003974692
Minimum0
Maximum60
Zeros1981
Zeros (%)16.1%
Negative0
Negative (%)0.0%
Memory size96.4 KiB
2022-11-15T11:50:30.872247image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median7
Q314
95-th percentile25
Maximum60
Range60
Interquartile range (IQR)12

Descriptive statistics

Standard deviation8.382558298
Coefficient of variation (CV)0.9309842137
Kurtosis0.9517735045
Mean9.003974692
Median Absolute Deviation (MAD)6
Skewness1.049586831
Sum111001
Variance70.26728362
MonotonicityNot monotonic
2022-11-15T11:50:31.074424image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
01981
 
16.1%
1946
 
7.7%
2717
 
5.8%
4571
 
4.6%
5563
 
4.6%
3537
 
4.4%
6517
 
4.2%
7503
 
4.1%
8500
 
4.1%
9471
 
3.8%
Other values (42)5022
40.7%
ValueCountFrequency (%)
01981
16.1%
1946
7.7%
2717
 
5.8%
3537
 
4.4%
4571
 
4.6%
5563
 
4.6%
6517
 
4.2%
7503
 
4.1%
8500
 
4.1%
9471
 
3.8%
ValueCountFrequency (%)
601
 
< 0.1%
541
 
< 0.1%
511
 
< 0.1%
491
 
< 0.1%
483
< 0.1%
471
 
< 0.1%
452
 
< 0.1%
441
 
< 0.1%
435
< 0.1%
425
< 0.1%

PP.1
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.531067489
Minimum0
Maximum48
Zeros6064
Zeros (%)49.2%
Negative0
Negative (%)0.0%
Memory size96.4 KiB
2022-11-15T11:50:31.256066image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q35
95-th percentile16
Maximum48
Range48
Interquartile range (IQR)5

Descriptive statistics

Standard deviation5.718002673
Coefficient of variation (CV)1.619341089
Kurtosis5.469852901
Mean3.531067489
Median Absolute Deviation (MAD)1
Skewness2.185048729
Sum43531
Variance32.69555457
MonotonicityNot monotonic
2022-11-15T11:50:31.457451image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
06064
49.2%
11259
 
10.2%
2695
 
5.6%
3528
 
4.3%
4470
 
3.8%
5390
 
3.2%
6361
 
2.9%
7309
 
2.5%
8278
 
2.3%
9253
 
2.1%
Other values (35)1721
 
14.0%
ValueCountFrequency (%)
06064
49.2%
11259
 
10.2%
2695
 
5.6%
3528
 
4.3%
4470
 
3.8%
5390
 
3.2%
6361
 
2.9%
7309
 
2.5%
8278
 
2.3%
9253
 
2.1%
ValueCountFrequency (%)
481
 
< 0.1%
451
 
< 0.1%
441
 
< 0.1%
411
 
< 0.1%
401
 
< 0.1%
392
< 0.1%
383
< 0.1%
371
 
< 0.1%
361
 
< 0.1%
351
 
< 0.1%

SH.1
Real number (ℝ≥0)

ZEROS

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2526768332
Minimum0
Maximum8
Zeros10042
Zeros (%)81.5%
Negative0
Negative (%)0.0%
Memory size96.4 KiB
2022-11-15T11:50:31.630347image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum8
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.6106004758
Coefficient of variation (CV)2.416527341
Kurtosis14.20072144
Mean0.2526768332
Median Absolute Deviation (MAD)0
Skewness3.176365451
Sum3115
Variance0.3728329411
MonotonicityNot monotonic
2022-11-15T11:50:31.807223image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
010042
81.5%
11673
 
13.6%
2453
 
3.7%
3123
 
1.0%
428
 
0.2%
65
 
< 0.1%
52
 
< 0.1%
71
 
< 0.1%
81
 
< 0.1%
ValueCountFrequency (%)
010042
81.5%
11673
 
13.6%
2453
 
3.7%
3123
 
1.0%
428
 
0.2%
52
 
< 0.1%
65
 
< 0.1%
71
 
< 0.1%
81
 
< 0.1%
ValueCountFrequency (%)
81
 
< 0.1%
71
 
< 0.1%
65
 
< 0.1%
52
 
< 0.1%
428
 
0.2%
3123
 
1.0%
2453
 
3.7%
11673
 
13.6%
010042
81.5%

S
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct345
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean81.27514601
Minimum0
Maximum528
Zeros397
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size96.4 KiB
2022-11-15T11:50:31.988324image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q119
median67
Q3126
95-th percentile218
Maximum528
Range528
Interquartile range (IQR)107

Descriptive statistics

Standard deviation71.19125018
Coefficient of variation (CV)0.8759289116
Kurtosis0.5005836051
Mean81.27514601
Median Absolute Deviation (MAD)52
Skewness0.9290648943
Sum1001960
Variance5068.194103
MonotonicityNot monotonic
2022-11-15T11:50:32.185906image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0397
 
3.2%
1356
 
2.9%
2280
 
2.3%
3267
 
2.2%
4204
 
1.7%
6189
 
1.5%
5155
 
1.3%
7133
 
1.1%
8126
 
1.0%
10123
 
1.0%
Other values (335)10098
81.9%
ValueCountFrequency (%)
0397
3.2%
1356
2.9%
2280
2.3%
3267
2.2%
4204
1.7%
5155
 
1.3%
6189
1.5%
7133
 
1.1%
8126
 
1.0%
9117
 
0.9%
ValueCountFrequency (%)
5281
< 0.1%
4461
< 0.1%
4251
< 0.1%
3981
< 0.1%
3951
< 0.1%
3921
< 0.1%
3861
< 0.1%
3721
< 0.1%
3682
< 0.1%
3671
< 0.1%

S_percent
Real number (ℝ≥0)

HIGH CORRELATION
MISSING
ZEROS

Distinct243
Distinct (%)2.0%
Missing124
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean7.527368076
Minimum0
Maximum100
Zeros2561
Zeros (%)20.8%
Negative0
Negative (%)0.0%
Memory size96.4 KiB
2022-11-15T11:50:32.379416image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.575
median7
Q311.1
95-th percentile16.7
Maximum100
Range100
Interquartile range (IQR)8.525

Descriptive statistics

Standard deviation7.557612092
Coefficient of variation (CV)1.004017874
Kurtosis52.50101745
Mean7.527368076
Median Absolute Deviation (MAD)4.2
Skewness4.929914511
Sum91864
Variance57.11750054
MonotonicityNot monotonic
2022-11-15T11:50:32.577059image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
02561
 
20.8%
8.3149
 
1.2%
10139
 
1.1%
7.1137
 
1.1%
11.1135
 
1.1%
6.3132
 
1.1%
7.7126
 
1.0%
12.5126
 
1.0%
9.1119
 
1.0%
5.6115
 
0.9%
Other values (233)8465
68.7%
(Missing)124
 
1.0%
ValueCountFrequency (%)
02561
20.8%
0.81
 
< 0.1%
0.94
 
< 0.1%
111
 
0.1%
1.118
 
0.1%
1.214
 
0.1%
1.313
 
0.1%
1.425
 
0.2%
1.528
 
0.2%
1.623
 
0.2%
ValueCountFrequency (%)
10028
0.2%
66.71
 
< 0.1%
5028
0.2%
46.21
 
< 0.1%
404
 
< 0.1%
33.347
0.4%
31.31
 
< 0.1%
303
 
< 0.1%
29.41
 
< 0.1%
28.65
 
< 0.1%

TOI
Real number (ℝ≥0)

HIGH CORRELATION

Distinct2044
Distinct (%)16.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean804.8196788
Minimum1
Maximum2412
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size96.4 KiB
2022-11-15T11:50:32.775548image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile19
Q1235
median812
Q31283
95-th percentile1727.65
Maximum2412
Range2411
Interquartile range (IQR)1048

Descriptive statistics

Standard deviation576.8075039
Coefficient of variation (CV)0.7166916008
Kurtosis-1.126884207
Mean804.8196788
Median Absolute Deviation (MAD)518
Skewness0.1727707787
Sum9921817
Variance332706.8966
MonotonicityNot monotonic
2022-11-15T11:50:32.973125image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1349
 
0.4%
748
 
0.4%
1246
 
0.4%
1444
 
0.4%
1144
 
0.4%
942
 
0.3%
841
 
0.3%
1940
 
0.3%
1540
 
0.3%
1839
 
0.3%
Other values (2034)11895
96.5%
ValueCountFrequency (%)
14
 
< 0.1%
23
 
< 0.1%
312
 
0.1%
415
 
0.1%
538
0.3%
633
0.3%
748
0.4%
841
0.3%
942
0.3%
1034
0.3%
ValueCountFrequency (%)
24121
< 0.1%
23781
< 0.1%
23751
< 0.1%
23451
< 0.1%
23101
< 0.1%
22971
< 0.1%
22521
< 0.1%
22491
< 0.1%
22401
< 0.1%
22391
< 0.1%

ATOI
Real number (ℝ≥0)

HIGH CORRELATION

Distinct1389
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.25178996
Minimum0
Maximum26.8
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size96.4 KiB
2022-11-15T11:50:33.366977image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5.489166666
Q110.96666667
median14.61666667
Q318
95-th percentile21.7775
Maximum26.8
Range26.8
Interquartile range (IQR)7.03333333

Descriptive statistics

Standard deviation4.980006486
Coefficient of variation (CV)0.3494302469
Kurtosis-0.1576869882
Mean14.25178996
Median Absolute Deviation (MAD)3.5
Skewness-0.4179602415
Sum175696.0667
Variance24.8004646
MonotonicityNot monotonic
2022-11-15T11:50:33.564577image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1730
 
0.2%
1630
 
0.2%
14.830
 
0.2%
13.329
 
0.2%
13.928
 
0.2%
16.728
 
0.2%
12.827
 
0.2%
13.827
 
0.2%
16.2833333327
 
0.2%
18.0666666727
 
0.2%
Other values (1379)12045
97.7%
ValueCountFrequency (%)
02
< 0.1%
0.0166666671
 
< 0.1%
0.0333333334
< 0.1%
0.054
< 0.1%
0.0666666673
< 0.1%
0.14
< 0.1%
0.1166666674
< 0.1%
0.1333333331
 
< 0.1%
0.152
< 0.1%
0.1666666673
< 0.1%
ValueCountFrequency (%)
26.82
< 0.1%
26.71
< 0.1%
26.51
< 0.1%
25.91
< 0.1%
25.71
< 0.1%
25.42
< 0.1%
25.32
< 0.1%
24.91
< 0.1%
24.82
< 0.1%
24.62
< 0.1%

BLK
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct219
Distinct (%)1.8%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean29.4438225
Minimum0
Maximum283
Zeros3216
Zeros (%)26.1%
Negative0
Negative (%)0.0%
Memory size96.4 KiB
2022-11-15T11:50:33.753419image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median15
Q341
95-th percentile119
Maximum283
Range283
Interquartile range (IQR)41

Descriptive statistics

Standard deviation38.98700971
Coefficient of variation (CV)1.324115091
Kurtosis3.513642162
Mean29.4438225
Median Absolute Deviation (MAD)15
Skewness1.864631106
Sum362954
Variance1519.986926
MonotonicityNot monotonic
2022-11-15T11:50:33.936979image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
03216
26.1%
1431
 
3.5%
2353
 
2.9%
3262
 
2.1%
4218
 
1.8%
5203
 
1.6%
6166
 
1.3%
13161
 
1.3%
17161
 
1.3%
7160
 
1.3%
Other values (209)6996
56.7%
ValueCountFrequency (%)
03216
26.1%
1431
 
3.5%
2353
 
2.9%
3262
 
2.1%
4218
 
1.8%
5203
 
1.6%
6166
 
1.3%
7160
 
1.3%
8151
 
1.2%
9156
 
1.3%
ValueCountFrequency (%)
2831
< 0.1%
2681
< 0.1%
2561
< 0.1%
2501
< 0.1%
2421
< 0.1%
2381
< 0.1%
2371
< 0.1%
2361
< 0.1%
2271
< 0.1%
2231
< 0.1%

HIT
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct297
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47.27052239
Minimum0
Maximum382
Zeros2875
Zeros (%)23.3%
Negative0
Negative (%)0.0%
Memory size96.4 KiB
2022-11-15T11:50:34.136645image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median30
Q375
95-th percentile156
Maximum382
Range382
Interquartile range (IQR)74

Descriptive statistics

Standard deviation54.32706299
Coefficient of variation (CV)1.149279937
Kurtosis2.556373903
Mean47.27052239
Median Absolute Deviation (MAD)30
Skewness1.506779626
Sum582751
Variance2951.429773
MonotonicityNot monotonic
2022-11-15T11:50:34.350008image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
02875
 
23.3%
1268
 
2.2%
3217
 
1.8%
2212
 
1.7%
4177
 
1.4%
6147
 
1.2%
5144
 
1.2%
7138
 
1.1%
10104
 
0.8%
8101
 
0.8%
Other values (287)7945
64.4%
ValueCountFrequency (%)
02875
23.3%
1268
 
2.2%
2212
 
1.7%
3217
 
1.8%
4177
 
1.4%
5144
 
1.2%
6147
 
1.2%
7138
 
1.1%
8101
 
0.8%
996
 
0.8%
ValueCountFrequency (%)
3821
< 0.1%
3741
< 0.1%
3651
< 0.1%
3641
< 0.1%
3591
< 0.1%
3561
< 0.1%
3431
< 0.1%
3361
< 0.1%
3181
< 0.1%
3111
< 0.1%

FOW
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct765
Distinct (%)6.2%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean62.3075363
Minimum0
Maximum1273
Zeros6860
Zeros (%)55.6%
Negative0
Negative (%)0.0%
Memory size96.4 KiB
2022-11-15T11:50:34.537544image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q314
95-th percentile474.7
Maximum1273
Range1273
Interquartile range (IQR)14

Descriptive statistics

Standard deviation160.3125024
Coefficient of variation (CV)2.572923147
Kurtosis9.866464874
Mean62.3075363
Median Absolute Deviation (MAD)0
Skewness3.133292465
Sum768065
Variance25700.09842
MonotonicityNot monotonic
2022-11-15T11:50:34.797830image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
06860
55.6%
1610
 
4.9%
2364
 
3.0%
3256
 
2.1%
4195
 
1.6%
5171
 
1.4%
7151
 
1.2%
6147
 
1.2%
8104
 
0.8%
1085
 
0.7%
Other values (755)3384
27.4%
ValueCountFrequency (%)
06860
55.6%
1610
 
4.9%
2364
 
3.0%
3256
 
2.1%
4195
 
1.6%
5171
 
1.4%
6147
 
1.2%
7151
 
1.2%
8104
 
0.8%
984
 
0.7%
ValueCountFrequency (%)
12731
< 0.1%
11751
< 0.1%
11301
< 0.1%
10861
< 0.1%
10831
< 0.1%
10631
< 0.1%
10391
< 0.1%
10291
< 0.1%
10261
< 0.1%
10241
< 0.1%

FOL
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct729
Distinct (%)5.9%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean62.30656283
Minimum0
Maximum941
Zeros6441
Zeros (%)52.2%
Negative0
Negative (%)0.0%
Memory size96.4 KiB
2022-11-15T11:50:34.986116image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q319
95-th percentile462
Maximum941
Range941
Interquartile range (IQR)19

Descriptive statistics

Standard deviation152.299919
Coefficient of variation (CV)2.444363998
Kurtosis8.021706307
Mean62.30656283
Median Absolute Deviation (MAD)0
Skewness2.910958278
Sum768053
Variance23195.26533
MonotonicityNot monotonic
2022-11-15T11:50:35.220850image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
06441
52.2%
1661
 
5.4%
2308
 
2.5%
3234
 
1.9%
4196
 
1.6%
5184
 
1.5%
6150
 
1.2%
7126
 
1.0%
8123
 
1.0%
10106
 
0.9%
Other values (719)3798
30.8%
ValueCountFrequency (%)
06441
52.2%
1661
 
5.4%
2308
 
2.5%
3234
 
1.9%
4196
 
1.6%
5184
 
1.5%
6150
 
1.2%
7126
 
1.0%
8123
 
1.0%
9105
 
0.9%
ValueCountFrequency (%)
9411
< 0.1%
9211
< 0.1%
9171
< 0.1%
9091
< 0.1%
9061
< 0.1%
9011
< 0.1%
8961
< 0.1%
8921
< 0.1%
8911
< 0.1%
8682
< 0.1%

FO_percent
Real number (ℝ≥0)

HIGH CORRELATION
MISSING
ZEROS

Distinct421
Distinct (%)3.5%
Missing311
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean21.63286178
Minimum0
Maximum100
Zeros6550
Zeros (%)53.1%
Negative0
Negative (%)0.0%
Memory size96.4 KiB
2022-11-15T11:50:35.425344image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q346.2
95-th percentile59.2
Maximum100
Range100
Interquartile range (IQR)46.2

Descriptive statistics

Standard deviation26.10006727
Coefficient of variation (CV)1.206500903
Kurtosis-0.2776320642
Mean21.63286178
Median Absolute Deviation (MAD)0
Skewness0.7983950431
Sum259962.1
Variance681.2135114
MonotonicityNot monotonic
2022-11-15T11:50:35.620430image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
06550
53.1%
50361
 
2.9%
100266
 
2.2%
33.3217
 
1.8%
40120
 
1.0%
25103
 
0.8%
66.785
 
0.7%
42.978
 
0.6%
28.668
 
0.6%
2065
 
0.5%
Other values (411)4104
33.3%
(Missing)311
 
2.5%
ValueCountFrequency (%)
06550
53.1%
6.71
 
< 0.1%
7.71
 
< 0.1%
8.32
 
< 0.1%
9.15
 
< 0.1%
9.71
 
< 0.1%
108
 
0.1%
10.51
 
< 0.1%
11.18
 
0.1%
11.83
 
< 0.1%
ValueCountFrequency (%)
100266
2.2%
87.51
 
< 0.1%
85.73
 
< 0.1%
84.61
 
< 0.1%
83.34
 
< 0.1%
81.81
 
< 0.1%
8011
 
0.1%
77.81
 
< 0.1%
7527
 
0.2%
73.31
 
< 0.1%

HART
Real number (ℝ≥0)

HIGH CORRELATION
SKEWED
ZEROS

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.001135626217
Minimum0
Maximum1
Zeros12314
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size96.4 KiB
2022-11-15T11:50:35.794896image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.03368127952
Coefficient of variation (CV)29.65877243
Kurtosis875.9282715
Mean0.001135626217
Median Absolute Deviation (MAD)0
Skewness29.62745631
Sum14
Variance0.00113442859
MonotonicityNot monotonic
2022-11-15T11:50:35.956480image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
012314
99.9%
114
 
0.1%
ValueCountFrequency (%)
012314
99.9%
114
 
0.1%
ValueCountFrequency (%)
114
 
0.1%
012314
99.9%

Votes
Real number (ℝ≥0)

HIGH CORRELATION
SKEWED
ZEROS

Distinct98
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.317083063
Minimum0
Maximum1604
Zeros12211
Zeros (%)99.1%
Negative0
Negative (%)0.0%
Memory size96.4 KiB
2022-11-15T11:50:36.137424image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1604
Range1604
Interquartile range (IQR)0

Descriptive statistics

Standard deviation53.89542281
Coefficient of variation (CV)16.24783636
Kurtosis435.3683345
Mean3.317083063
Median Absolute Deviation (MAD)0
Skewness20.04010988
Sum40893
Variance2904.7166
MonotonicityNot monotonic
2022-11-15T11:50:36.326280image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
012211
99.1%
14
 
< 0.1%
173
 
< 0.1%
283
 
< 0.1%
12642
 
< 0.1%
312
 
< 0.1%
322
 
< 0.1%
1572
 
< 0.1%
10582
 
< 0.1%
532
 
< 0.1%
Other values (88)95
 
0.8%
ValueCountFrequency (%)
012211
99.1%
14
 
< 0.1%
21
 
< 0.1%
31
 
< 0.1%
41
 
< 0.1%
92
 
< 0.1%
102
 
< 0.1%
121
 
< 0.1%
161
 
< 0.1%
173
 
< 0.1%
ValueCountFrequency (%)
16041
< 0.1%
14731
< 0.1%
13951
< 0.1%
13401
< 0.1%
13131
< 0.1%
12642
< 0.1%
12251
< 0.1%
11941
< 0.1%
11041
< 0.1%
10901
< 0.1%

Season
Real number (ℝ≥0)

HIGH CORRELATION

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2011.438595
Minimum2004
Maximum2018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size96.4 KiB
2022-11-15T11:50:36.704422image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum2004
5-th percentile2004
Q12008
median2012
Q32015
95-th percentile2018
Maximum2018
Range14
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.170861195
Coefficient of variation (CV)0.002073571227
Kurtosis-1.089619402
Mean2011.438595
Median Absolute Deviation (MAD)4
Skewness-0.1059065838
Sum24797015
Variance17.39608311
MonotonicityNot monotonic
2022-11-15T11:50:36.878525image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
2004916
 
7.4%
2016898
 
7.3%
2012894
 
7.3%
2011891
 
7.2%
2018890
 
7.2%
2017888
 
7.2%
2014886
 
7.2%
2009885
 
7.2%
2015882
 
7.2%
2010879
 
7.1%
Other values (4)3419
27.7%
ValueCountFrequency (%)
2004916
7.4%
2006870
7.1%
2007858
7.0%
2008852
6.9%
2009885
7.2%
2010879
7.1%
2011891
7.2%
2012894
7.3%
2013839
6.8%
2014886
7.2%
ValueCountFrequency (%)
2018890
7.2%
2017888
7.2%
2016898
7.3%
2015882
7.2%
2014886
7.2%
2013839
6.8%
2012894
7.3%
2011891
7.2%
2010879
7.1%
2009885
7.2%

Interactions

2022-11-15T11:50:17.796047image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:47:54.521173image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:00.143592image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:05.372873image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:10.433099image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:15.603028image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:20.705339image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:25.852340image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:30.996723image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:36.161793image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:41.486582image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:46.614054image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:51.883588image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:57.112150image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:02.631939image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:08.083385image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:13.503095image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:18.763962image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:23.975430image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:29.185444image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:34.415767image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:39.631402image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:45.107069image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:50.796345image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:56.095412image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:01.330865image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:06.706398image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:12.225593image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:17.975902image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:47:54.843190image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:00.315914image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:05.540299image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:10.614405image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:15.782166image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:20.881373image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:26.025775image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:31.171250image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:36.350491image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:41.654601image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:46.791118image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:52.054469image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:57.292361image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:02.802092image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:08.282583image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:13.683535image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:18.931860image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:24.200378image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:29.361800image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:34.595406image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:39.811880image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:45.288100image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:50.966084image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:56.268098image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:01.514365image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:06.902059image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:12.399782image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:18.161614image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:47:55.102411image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:00.661870image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:05.705626image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:10.811003image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:15.952905image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:21.060972image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:26.201208image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:31.342049image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:36.521950image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:41.830567image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:46.965582image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:52.235953image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:57.471227image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:02.993402image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:08.661004image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:13.857900image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:19.112036image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:24.375999image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:29.540210image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:34.771060image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:39.990238image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:45.494687image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:51.155882image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:56.457721image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:01.696043image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:07.107159image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:12.582536image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:18.345893image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:47:55.314076image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:00.833779image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:05.881683image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:10.981896image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:16.135232image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:21.233135image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:26.371316image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:31.520986image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:36.703863image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:42.001777image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:47.133673image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:52.414409image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:57.651297image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:03.205242image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:08.835511image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:14.032625image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:19.290327image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:24.550200image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:29.723416image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:34.945355image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:40.162992image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:45.689403image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:51.330491image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:56.636446image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:01.875389image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:07.294485image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:12.965348image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:18.518492image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:47:55.644099image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:01.022042image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:06.057790image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:11.185487image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:16.320198image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:21.413756image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:26.541173image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:31.695406image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:36.890928image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:42.181197image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:47.321134image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:52.593828image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:57.830363image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:03.581201image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:09.011544image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:14.213706image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:19.462170image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:24.721380image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:29.895286image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:35.130537image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:40.342877image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:45.927389image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:51.516088image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:56.819759image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:02.055983image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:07.505984image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:13.152682image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:18.697806image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:47:55.875406image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:01.192383image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:06.222986image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:11.356813image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:16.485517image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:21.584109image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:26.713350image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:31.877417image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:37.071966image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:42.353121image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:47.490956image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:52.771671image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:58.002014image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:03.753541image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:09.190996image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:14.394580image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:19.665515image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:24.896277image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:30.061005image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:35.300562image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:40.513367image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:46.105607image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:51.695551image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:57.004418image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:02.239697image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:07.919708image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:13.344482image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:18.875627image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:47:56.045598image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:01.363640image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:06.391047image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:11.531317image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:16.652409image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:21.764787image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:26.890943image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:32.051325image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:37.260362image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:42.532236image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:47.671160image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:52.951971image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:58.375931image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:03.981327image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:09.371955image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:14.575327image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:19.840348image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:25.076001image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:30.251145image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:35.476235image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:40.693846image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:46.289198image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:51.885125image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:57.186448image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:02.429575image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:08.092916image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:13.525424image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:19.048654image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:47:56.265984image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:01.527078image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:06.563516image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:11.698395image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:16.832681image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:21.936294image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:27.065317image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:32.221390image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:37.461016image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:42.713575image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:47.848462image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:53.132671image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:58.548516image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:04.151111image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:09.541500image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:14.753124image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:20.004247image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:25.250928image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:30.430120image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:35.648973image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:40.941128image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:46.479675image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:52.069538image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:57.355600image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:02.806134image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:08.267237image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:13.699539image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:19.235342image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:47:56.434549image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:01.701705image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:06.731244image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:11.880177image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:17.003516image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:22.111384image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:27.240126image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:32.408104image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:37.637114image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:42.897006image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:48.021871image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:53.312078image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:58.720350image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:04.321870image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:09.711826image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:14.932427image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:20.192905image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:25.432990image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:30.608882image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:35.833505image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:41.198915image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:46.676249image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:52.258869image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:57.746267image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:02.989100image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:08.489489image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:13.886453image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:19.416937image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:47:56.628582image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:01.881037image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:06.902253image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:12.059356image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:17.185244image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:22.292713image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:27.422885image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:32.592114image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:37.826236image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:43.081701image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:48.231733image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:53.697974image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:58.902118image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:04.502946image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:09.895427image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:15.117336image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:20.382756image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:25.613518image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:30.792183image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:36.022298image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:41.408431image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:46.875138image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:52.440489image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:57.927679image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:03.175078image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:08.667668image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:14.068301image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:19.591044image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:47:56.842110image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:02.050914image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:07.071005image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:12.231946image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:17.352671image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:22.470973image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:27.592787image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:32.772227image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:38.001059image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:43.257866image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:48.406938image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:53.871387image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:59.078713image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:04.682444image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:10.070402image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:15.292885image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:20.559185image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:25.785294image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:30.970261image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:36.201260image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:41.603079image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:47.055811image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:52.826583image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:58.104762image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:03.345413image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:08.841530image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:14.250039image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:19.774526image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:47:57.008718image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:02.221326image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:07.241098image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:12.411826image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:17.528405image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:22.641900image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:27.765385image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:32.951155image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:38.212171image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:43.431248image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:48.831819image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:54.047743image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:59.251303image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:04.912000image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:10.261381image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:15.476691image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:20.756572image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:25.961285image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:31.151345image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:36.376942image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:41.798261image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:47.239425image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:53.008091image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:58.274460image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:03.519789image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:09.034424image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:14.439600image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:19.957675image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:47:57.191066image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:02.402021image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:07.414193image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:12.592240image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:17.710914image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:22.821970image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:27.941842image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:33.131980image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:38.401320image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:43.612212image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:49.003927image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:54.230534image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:59.425547image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:05.091331image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:10.440524image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:15.655598image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:20.937891image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:26.143099image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:31.333026image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:36.564727image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:41.997956image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:47.429145image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:53.197476image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:58.448094image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:03.701087image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:09.247393image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:14.624483image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:20.145491image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:47:57.420992image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:02.571365image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:07.593633image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:12.764128image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:17.880901image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:22.997744image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:28.112246image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:33.305275image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:38.574201image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:43.990105image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:49.182796image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:54.405316image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:59.603679image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:05.269528image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:10.623005image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:15.835809image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:21.113034image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:26.321318image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:31.533632image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:36.743074image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:42.177265image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:47.820553image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:53.369397image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:58.626169image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:03.879401image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:09.427418image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:14.809880image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:20.357643image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:47:57.587882image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:02.746497image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:07.774198image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:12.950435image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:18.058063image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:23.174878image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:28.296848image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:33.485757image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:38.759207image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:44.164797image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:49.351770image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:54.592253image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:59.783595image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:05.441298image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:10.800135image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:16.021327image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:21.290990image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:26.501834image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:31.715164image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:36.932115image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:42.366678image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:48.007040image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:53.547695image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:58.804592image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:04.064525image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:09.614450image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:14.995434image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:20.537559image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:47:57.765367image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:02.927951image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:07.944834image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:13.121930image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:18.240554image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:23.348647image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:28.476532image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:33.661690image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:39.131051image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:44.341303image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:49.535313image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:54.771177image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:59.975766image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:05.617072image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:10.971992image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:16.202142image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:21.472013image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:26.673311image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:31.891213image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:37.107323image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:42.755567image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:48.187291image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:53.726917image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:58.975527image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:04.237700image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:09.834344image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:15.166443image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:20.724358image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:47:58.001154image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:03.104107image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:08.117211image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:13.301088image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:18.421240image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:23.531475image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:28.661156image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:33.841132image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:39.313186image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:44.513503image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:49.710447image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:54.944330image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:00.200988image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:05.802286image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:11.165886image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:16.383534image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:21.651371image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:26.861046image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:32.072933image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:37.287794image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:42.935672image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:48.426218image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:53.906184image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:59.156716image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:04.426094image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:10.019935image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:15.355145image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:20.905143image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:47:58.206759image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:03.284711image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:08.282078image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:13.471072image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:18.593029image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:23.702124image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:28.836951image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:34.015102image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:39.490093image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:44.692087image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:49.881101image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:55.124329image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:00.431229image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:05.975712image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:11.340105image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:16.561953image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:21.827172image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:27.032706image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:32.253464image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:37.663242image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:43.123103image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:48.602139image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:54.085378image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:59.365920image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:04.605372image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:10.204630image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:15.541960image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:21.095465image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:47:58.377731image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:03.454597image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:08.464181image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:13.643201image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:18.773534image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:23.885361image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:29.011135image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:34.381408image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:39.663285image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:44.861673image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:50.060962image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:55.313645image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:00.634923image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:06.151961image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:11.512228image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:16.744841image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:22.005355image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:27.211665image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:32.431610image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:37.835003image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:43.296665image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:48.806066image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:54.266481image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:59.542641image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:04.779257image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:10.379456image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:15.722654image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:21.268804image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:47:58.541143image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:03.622001image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:08.643863image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:13.811058image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:18.951203image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:24.061233image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:29.181997image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:34.561682image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:39.845571image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:45.030887image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:50.231221image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:55.490349image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:00.843356image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:06.371110image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:11.691262image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:16.920469image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:22.180907image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:27.391389image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:32.814554image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:38.011154image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:43.480437image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:49.066310image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:54.436024image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:59.717010image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:04.957946image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:10.569919image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:15.896307image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:21.448367image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:47:58.762077image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:03.795624image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:08.820648image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:13.981411image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:19.120985image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:24.232395image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:29.555346image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:34.740414image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:40.031234image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:45.201892image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:50.401002image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:55.667854image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:01.058476image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:06.544018image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:11.864615image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:17.095687image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:22.351101image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:27.569351image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:33.001150image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:38.190261image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:43.660268image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:49.245591image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:54.616822image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:59.897186image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:05.136221image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:10.787259image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:16.089583image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:21.675843image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:47:58.922011image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:03.960372image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:08.991377image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:14.163382image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:19.292318image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:24.599539image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:29.721754image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:34.909917image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:40.213486image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:45.370326image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:50.582849image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:55.843983image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:01.261407image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:06.716334image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:12.051274image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:17.281100image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:22.527055image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:27.946280image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:33.173101image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:38.367718image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:43.836537image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:49.416478image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:54.815520image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:00.074450image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:05.327879image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:10.964780image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:16.277370image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:21.854624image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:47:59.102226image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:04.132390image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:09.173784image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:14.341285image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:19.471109image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:24.778926image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:29.901284image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:35.091978image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:40.398226image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:45.551075image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:50.760971image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:56.031412image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:01.441674image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:06.901297image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:12.237728image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:17.461792image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:22.713855image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:28.135950image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:33.353465image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:38.541235image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:44.023803image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:49.616288image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:54.994734image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:00.247381image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:05.525256image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:11.146321image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:16.459308image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:22.035350image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:47:59.273739image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:04.303712image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:09.350439image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:14.521893image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:19.837955image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:24.956871image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:30.073568image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:35.270499image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:40.571752image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:45.727154image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:50.955320image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:56.210972image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:01.666770image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:07.080291image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:12.411344image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:17.636309image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:23.090319image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:28.311241image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:33.531024image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:38.721639image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:44.196303image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:49.796140image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:55.177545image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:00.425134image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:05.697080image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:11.326181image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:16.641537image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:22.215972image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:47:59.441654image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:04.480199image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:09.519609image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:14.705791image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:20.004839image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:25.135421image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:30.240927image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:35.442584image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:40.753698image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:45.910448image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:51.124826image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:56.383745image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:01.851022image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:07.252446image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:12.585653image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:17.818140image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:23.271202image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:28.481215image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:33.701109image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:38.898185image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:44.367938image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:49.979753image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:55.350692image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:00.598297image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:05.865261image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:11.504760image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:16.816505image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:22.594594image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:47:59.612261image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:04.651923image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:09.692111image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:15.075888image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:20.181959image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:25.312166image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:30.415414image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:35.621628image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:40.940319image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:46.081978image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:51.303587image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:56.565649image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:02.033286image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:07.434173image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:12.762018image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:18.213037image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:23.442743image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:28.652989image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:33.873101image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:39.080191image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:44.555140image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:50.168446image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:55.529294image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:00.777437image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:06.047215image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:11.676854image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:17.045492image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:22.774726image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:47:59.792935image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:04.831109image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:09.861366image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:15.251276image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:20.350391image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:25.483108image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:30.591279image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:35.801002image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:41.111635image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:46.265468image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:51.505357image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:56.742099image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:02.210988image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:07.622068image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:12.941299image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:18.397089image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:23.613053image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:28.825735image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:34.050126image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:39.257335image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:44.745519image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:50.353021image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:55.718551image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:00.959232image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:06.235097image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:11.857749image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:17.225988image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:22.957322image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:47:59.971991image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:05.006051image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:10.251256image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:15.423665image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:20.531351image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:25.666060image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:30.815132image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:35.991539image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:41.302813image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:46.442100image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:51.683439image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:48:56.925274image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:02.451148image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:07.841796image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:13.121163image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:18.582126image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:23.796941image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:29.007867image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:34.223238image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:39.440517image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:44.927104image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:50.573653image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:49:55.908587image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:01.148538image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:06.477369image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:12.035909image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-11-15T11:50:17.410767image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Correlations

2022-11-15T11:50:37.092322image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Auto

The auto setting is an easily interpretable pairwise column metric of the following mapping: vartype-vartype : method, categorical-categorical : Cramer's V, numerical-categorical : Cramer's V (using a discretized numerical column), numerical-numerical : Spearman's ρ. This configuration uses the best suitable for each pair of columns.
2022-11-15T11:50:37.359127image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-11-15T11:50:37.625138image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-11-15T11:50:37.896330image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-11-15T11:50:38.127521image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.
2022-11-15T11:50:38.337286image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-11-15T11:50:23.255195image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
A simple visualization of nullity by column.
2022-11-15T11:50:23.756468image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-11-15T11:50:24.057435image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-11-15T11:50:24.276756image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

RkPlayerNickAgePosTmGPGAPTSplusminusPIMPSEVPPSHGWEV.1PP.1SH.1SS_percentTOIATOIBLKHITFOWFOLFO_percentHARTVotesSeason
01Connor McDavidmcdavco0120CEDM823070100272612.8263164524125112.0173321.13333329.034348.0458.043.2116042017
12Sidney Crosbycrosbsi0129CPIT75444589172412.33014053411025517.3149119.88333327.080842.0906.048.2011042017
23Patrick Kanekanepa0128RWCHI82345589113210.8277053916029211.6175421.40000015.0287.044.013.702062017
34Nicklas Backstrombacksni0229CWSH8223638617389.9158053627016214.2149718.26666733.045685.0648.051.40602017
45Nikita Kucherovkucheni0123RWTBL74404585133812.02317073015024616.3143819.43333320.0300.00.00.001192017
56Brad Marchandmarchbr0328LWBOS80394685188112.6279382915222617.3155519.43333335.05113.023.036.101842017
67Mark Scheifelescheima0123CWPG79325082183810.325705408216020.0162420.56666734.049635.0826.043.5002017
78Leon Draisaitldraisle0121CEDM822948777209.61910053117017216.9154818.88333336.041476.0496.049.0002017
89Brent Burnsburnsbr0131DSJS82294776194015.321806291713209.120390.866667142.0690.00.00.002732017
910Vladimir Tarasenkotarasvl0125RWSTL82393675-11210.2309082313028613.6151518.46666731.0505.05.050.0002017

Last rows

RkPlayerNickAgePosTmGPGAPTSplusminusPIMPSEVPPSHGWEV.1PP.1SH.1SS_percentTOIATOIBLKHITFOWFOLFO_percentHARTVotesSeason
12318881Carson Soucysoucyca0123DMIN3000-22-0.1000000040.04514.93.040.00.0NaN002018
12319882Mark Streitstreima0140DMTL2000-20-0.1000000030.02814.20.020.00.0NaN002018
12320883Matt Tennysontennyma0127DBUF15000-88-0.20000000250.027018.011.0130.00.0NaN002018
12321884Troy Terryterrytr0120CANA2000000.0000000030.02010.22.000.00.0NaN002018
12322885Eeli Tolvanentolvaee0118RWNSH300000-0.1000000030.03612.11.020.00.0NaN002018
12323886Zach Trotmantrotmza0127DPIT3000-30-0.2000000060.03812.82.010.00.0NaN002018
12324887Dominic Turgeonturgedo0121CDET5000-22-0.2000000030.0469.28.037.014.033.3002018
12325888Rinat Valievvalieri0122DMTL2000020.0000000020.02411.82.000.00.0NaN002018
12326889Curtis Valkvalkcu0124LWFLA1000000.000000000NaN33.40.010.03.00.0002018
12327890Zach Whitecloudwhiteza0121DVEG1000300.200000000NaN1716.71.000.00.0NaN002018